getting a list of coordinates from a 2D matrix

Question

Let's say I have a 10 x 20 matrix of values (so 200 data points)

values = np.random.rand(10,20)

with a known regular spacing between coordinates so that the x and y coordinates are defined by

coord_x = np.arange(0,5,0.5)  --> gives [0.0,0.5,1.0,1.5...4.5]
coord_y = np.arange(0,5,0.25) --> gives [0.0,0.25,0.50,0.75...4.5]

I'd like to get an array representing each coordinates points so that the shape of the array is (200,2), 200 being the total number of points and the extra dimension simply representing x and y such as

coord[0][0]=0.0, coord[0][1]=0.0
coord[1][0]=0.0, coord[1][1]=0.25
coord[2][0]=0.0, coord[2][1]=0.50
...
coord[19][0]=0.0, coord[19][1]=5.0
coord[20][0]=0.5, coord[20][1]=0.0
coord[21][0]=0.5, coord[21][1]=0.25
coord[22][0]=0.5, coord[22][1]=0.50
...
coord[199][0]=4.5, coord[199][1]=4.5

That would a fairly easy thing to do with a double for loop, but I wonder if there is more elegant solution using built-in numpy (or else) functions.

?

wim · Accepted Answer · 2014-05-16 13:39:28Z

I think meshgrid may be what you're looking for.

Here's an example, with smaller number of datapoints:

>>> from numpy import fliplr, dstack, meshgrid, linspace
>>> x, y, nx, ny = 4.5, 4.5, 3, 10
>>> Xs = linspace(0, x, nx)
>>> Ys = linspace(0, y, ny)
>>> fliplr(dstack(meshgrid(Xs, Ys)).reshape(nx * ny, 2))

array([[ 0.  ,  0.  ],
       [ 0.  ,  2.25],
       [ 0.  ,  4.5 ],
       [ 0.5 ,  0.  ],
       [ 0.5 ,  2.25],
       [ 0.5 ,  4.5 ],
       [ 1.  ,  0.  ],
       [ 1.  ,  2.25],
       [ 1.  ,  4.5 ],
       [ 1.5 ,  0.  ],
       [ 1.5 ,  2.25],
       [ 1.5 ,  4.5 ],
       [ 2.  ,  0.  ],
       [ 2.  ,  2.25],
       [ 2.  ,  4.5 ],
       [ 2.5 ,  0.  ],
       [ 2.5 ,  2.25],
       [ 2.5 ,  4.5 ],
       [ 3.  ,  0.  ],
       [ 3.  ,  2.25],
       [ 3.  ,  4.5 ],
       [ 3.5 ,  0.  ],
       [ 3.5 ,  2.25],
       [ 3.5 ,  4.5 ],
       [ 4.  ,  0.  ],
       [ 4.  ,  2.25],
       [ 4.  ,  4.5 ],
       [ 4.5 ,  0.  ],
       [ 4.5 ,  2.25],
       [ 4.5 ,  4.5 ]])

gg349 · Accepted Answer · 2014-05-16 13:26:17Z

1

I think you meant coord_y = np.arange(0,5,0.25) in your question. You can do

from numpy import meshgrid,column_stack
x,y=meshgrid(coord_x,coord_y)
coord = column_stack((x.T.flatten(),y.T.flatten()))

answered May 16, 2014 at 13:26

gg349

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